Perceptual learning refers to remarkable
performance improvement after intensive training. It is a popular model for
studying cortical plasticity. So far, we still do not know much about the
neural mechanisms of visual perceptual learning. There is a debate between
early-stage theories and late-stage theories. Early-stage theories argue that
perceptual learning sharpens the tuning properties of early visual neurons.
Late-stage theories argue that perceptual learning reweights the outputs of
visual channels for optimal decision making. In my lab, we combined
psychophysics, magnetic resonance imaging, and transcranical magnetic
stimulation to investigate the neural mechanisms of face and motion
discrimination learning. We show that: 1) perceptual learning reduces internal
neural noise and sharpens cortical tuning to trained stimuli in sensory coding
areas; 2) perceptual learning modifies the connections between sensory and
higher areas for optimal decision-making; 3) The anatomical structure of
sensory cortex could predict the effect of perceptual training; 4) The effects
of perceptual learning extend beyond the retuning of specific neural
populations that mediate performance of the trained task. Learning could modify
the inherent functional specializations of visual cortical areas.